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Singularity in a two-point complex coherence function, known as coherence vortices, represents zero visibility with a helical phase structure. In this paper, we introduce a novel technique to generate the coherence vortices of different topological charges by incoherent source transmittance with exotic structured binary pinholes. The binary pinhole structures have been realized by lithography, followed by wet etching methods. We control the transmittance from the incoherent source plane using these exotic apertures, which finally results in a coherence vortex spectrum that features multiple and pure orbital angular momentum modes. The generation of the coherence vortices is achieved within the two-point complex spatial coherence function. The spatial coherence function exhibits the helical phase profile in its phase part, and its absolute part shows a doughnut-shaped structure. A theoretical basis is developed and validated with simulation, and experimental results. The coherence vortex spectra with OAM modes superposed with opposite topological charges, known as photonic gears, are also generated with the proposed theory. [ABSTRACT FROM AUTHOR]

Ultrasonic phased array detection technology is a promising non-destructive testing (NDT) method that has been widely used for defect detection. Due to the high attenuation characteristics of ultrasonic wave propagation in carbon fibre reinforced polymer (CFRP) and the directivity of the array elements, the possibility of false or missed detection for defects that are far from the array elements or located very close together will increase. In addition, the total focusing method (TFM) employs only the defect information contained in the full matrix capture (FMC) dataset while ignoring the spatial information of the array signals, leading to image mixed with artefact and noise. An improved method called p-weighted-TFM (p-WTFM) is proposed. First, this method scales the magnitude of time-delayed channel signal by p-th root while maintaining the phase unchanged. Second, channel summation with energy compensation and directional correction will be realised. Finally, the signal dimensionality is restored by p-th power. Experimental results show that the p-WTFM can use any rational p-value to flexibly adjust image quality. Specially, this method can accurately distinguish adjacent defects spaced 1 mm apart with p value of 2.5, and it can also detect two defects located 10 mm deep with p value of 3.0. [ABSTRACT FROM AUTHOR]

Rapid and accurate bacterial identification is essential for timely treatment of infections like sepsis. While traditional methods are reliable, they lack speed, and advanced molecular techniques often suffer from cost and complexity. The bacterial detection technology based on optical scattering system offers a rapid, label-free alternative but traditionally relies on complex lasers and analysis. Our enhanced approach utilizes RGB light emitting diodes (LEDs) as the light source. Three diffraction images of bacterial colonies from different LED colors are separately captured by a USB camera and combined using an image registration algorithm to enhance image sharpness. Our approach utilizes an object detection model, i.e., YOLOv8, for analysis achieving high-accuracy differentiation between bacterial strains. We demonstrate the effectiveness of this approach, achieving an average accuracy of 97% (mAP50 of 0.97), including accurate discrimination of closely related strains and the significant pathogen Staphylococcus aureus MRSA 1320. Our enhancement offers advantages in affordability, usability, and seamless integration into existing workflows, providing an alternative for rapid bacterial identification. [ABSTRACT FROM AUTHOR]

Abstract Rapid and accurate bacterial identification is essential for timely treatment of infections like sepsis. While traditional methods are reliable, they lack speed, and advanced molecular techniques often suffer from cost and complexity. The bacterial detection technology based on optical scattering system offers a rapid, label-free alternative but traditionally relies on complex lasers and analysis. Our enhanced approach utilizes RGB light emitting diodes (LEDs) as the light source. Three diffraction images of bacterial colonies from different LED colors are separately captured by a USB camera and combined using an image registration algorithm to enhance image sharpness. Our approach utilizes an object detection model, i.e., YOLOv8, for analysis achieving high-accuracy differentiation between bacterial strains. We demonstrate the effectiveness of this approach, achieving an average accuracy of 97% (mAP50 of 0.97), including accurate discrimination of closely related strains and the significant pathogen Staphylococcus aureus MRSA 1320. Our enhancement offers advantages in affordability, usability, and seamless integration into existing workflows, providing an alternative for rapid bacterial identification.

In the northern high latitudes, warmer spring temperatures generally lead to earlier leaf onsets, higher vegetation production, and enhanced spring carbon uptake. Yet, whether this positive linkage has diminished under climate change remains debated. Here, we used atmospheric CO2 measurements at Barrow (Alaska) during 1979–2020 to investigate the strength of temperature dependence of spring carbon uptake reflected by two indicators, spring zero‐crossing date (SZC) and CO2 drawdown (SCC). We found a fall and rise in the interannual correlation of temperature with SZC and SCC (RSZC‐T and RSCC‐T), showing a recent reversal of the previously reported weakening trend of RSZC‐T and RSCC‐T. We used a terrestrial biosphere model coupled with an atmospheric transport model to reproduce this fall and rise phenomenon and conducted factorial simulations to explore its potential causes. We found that a strong–weak–strong spatial synchrony of spring temperature anomalies per se has contributed to the fall and rise trend in RSZC‐T and RSCC‐T, despite an overall unbroken temperature control on net ecosystem CO2 fluxes at local scale. Our results provide an alternative explanation for the apparent drop of RSZC‐T and RSCC‐T during the late 1990s and 2000s, and suggest a continued positive linkage between spring carbon uptake and temperature during the past four decades. We thus caution the interpretation of apparent climate sensitivities of carbon cycle retrieved from spatially aggregated signals. [ABSTRACT FROM AUTHOR]

The possibility of improving the quality of X-ray images formed using diffraction on a two-block crystalline system is considered. It is shown that the low spatial coherence of the initial radiation improves imaging quality. Conventional wide-focus X-ray tubes can be used as a source for such radiation. The feasibility of using a scanning scheme to reduce the background level in the formed image was also considered by numerical simulation. [ABSTRACT FROM AUTHOR]

Abstract A three-stage approach is proposed for speaker counting and speech separation in noisy and reverberant environments. In the spatial feature extraction, a spatial coherence matrix (SCM) is computed using whitened relative transfer functions (wRTFs) across time frames. The global activity functions of each speaker are estimated from a simplex constructed using the eigenvectors of the SCM, while the local coherence functions are computed from the coherence between the wRTFs of a time-frequency bin and the global activity function-weighted RTF of the target speaker. In speaker counting, we use the eigenvalues of the SCM and the maximum similarity of the interframe global activity distributions between two speakers as the input features to the speaker counting network (SCnet). In speaker separation, a global and local activity-driven network (GLADnet) is used to extract each independent speaker signal, which is particularly useful for highly overlapping speech signals. Experimental results obtained from the real meeting recordings show that the proposed system achieves superior speaker counting and speaker separation performance compared to previous publications without the prior knowledge of the array configurations.

In the recent decade, the rotational Doppler effect has garnered considerable attention for stimulating the development of applications such as rotational Doppler velocity and topological charge measurements. Previous studies performed measurements under sources with one or multiple amplitude, phase, and polarization modulations. However, the applicability of these schemes is limited by the crucial factor of alignment between the source and object, especially if the magnitude of the source is greater than the object size. Therefore, this study proposes a partially coherent angular velocity measurement model that allows the rotational axes of targets to deviate from the source center and is even less susceptible to external jitters. Accordingly, a proof‐of‐principle experiment to determine the angular velocity under arbitrary alignment conditions is conducted. Tracing the rotational motion by rotating the coherent structure of the source results in a frequency shift—red shift for the same rotation and blue shift for a reverse rotation. The angular velocity vectors (both magnitude and direction) of two anisotropic sub‐Rayleigh objects are successfully measured with ultrahigh precision. The lowest angular velocity is 0.001 r s−1. The average relative error is less than 0.05% with sufficient sampling. Thus, the present findings can be applied to velocity metrology and micromanipulation. [ABSTRACT FROM AUTHOR]

A three-stage approach is proposed for speaker counting and speech separation in noisy and reverberant environments. In the spatial feature extraction, a spatial coherence matrix (SCM) is computed using whitened relative transfer functions (wRTFs) across time frames. The global activity functions of each speaker are estimated from a simplex constructed using the eigenvectors of the SCM, while the local coherence functions are computed from the coherence between the wRTFs of a time-frequency bin and the global activity function-weighted RTF of the target speaker. In speaker counting, we use the eigenvalues of the SCM and the maximum similarity of the interframe global activity distributions between two speakers as the input features to the speaker counting network (SCnet). In speaker separation, a global and local activity-driven network (GLADnet) is used to extract each independent speaker signal, which is particularly useful for highly overlapping speech signals. Experimental results obtained from the real meeting recordings show that the proposed system achieves superior speaker counting and speaker separation performance compared to previous publications without the prior knowledge of the array configurations. [ABSTRACT FROM AUTHOR]

Many spatial applications benefit from the fast answering to a seemingly simple spatial query: "Is a point of interest (POI) 'in-path' to the shortest path between a source and a destination?" In this context, an in-path POI is one that is either on the shortest path or can be reached within a bounded yet small detour from the shortest path. The fast answering of the in-path queries is contingent on being able to determine without having to actually compute the shortest paths during runtime. Thus, this requires a precomputation solution. The key contribution of the paper is the development of an in-path oracle that is based on precomputation of which pairs of sources and destinations are in-path with respect to the given POI. For a given road network with n nodes and m POIs, an O (m × n) -sized oracle is envisioned based on the reduction of the well-separated pairs (WSP) decomposition of the road network. Furthermore, an oracle can be indexed in a database using a B-tree that can answer queries at very high throughput. Experimental results on the real road network POI dataset illustrate the superiority of this technique compared to a baseline algorithm. The proposed approach can answer ≈ 1.5 million in-path queries per second compared to a few hundred per second using a suitable baseline approach. [ABSTRACT FROM AUTHOR]

Abstract Wind tunnel tests remain crucial to solving the wind-induced issues, such as buffeting. The turbulence impacts on the aerodynamic forces is vital to buffeting responses of a bridge, which has been neglected, for that traditional passive wind tunnel test simulations are mainly to perform smaller turbulence integral scale, compared with the reduced-scale similarity. A turbulence hybrid simulation device that integrates vibrating grids and active fans was proposed, realizing a detectable adjustment of the bi-directional pulse energy of the incoming turbulence. The simulation development of the active turbulence in the wind tunnel test was reviewed briefly firstly. To investigate turbulence influence on the aerodynamic forces, the pressure-measurement wind tunnel tests of typical bridge decks were carried out in active control wind tunnel. The impacts of different incoming turbulence on the aerodynamic force and buffeting response were furtherly discussed. Results revealed that the bi-direction (along-wind and vertical wind) influenced aerodynamic forces synergistically. Otherwise, turbulence integral scale strongly influenced aerodynamic characteristics, such as buffeting responses, notably, the buffeting responses obtained in active controlled wind tunnel would be reasonable for a safety evaluation of bridges under construction and operation.

The frequency-difference and frequency-sum autoproducts, quadratic products of complex acoustic field amplitudes at two frequencies, may mimic genuine acoustic fields at the difference and sum frequencies of the constituent fields, respectively. Autoproducts have proven useful in extending the useable frequency range for acoustic remote sensing to frequencies outside a recorded field’s bandwidth. In array signal processing applications, the spatial coherence of the field often sets performance limits. This paper presents results for the spatial coherence of the genuine field, the frequency-difference autoproduct, and the frequency-sum autoproduct as determined from data collected during the Cascadia Open-Access Seismic Transects (COAST 2012) experiment. In this experiment, an airgun array providing a 10 to 200 Hz signal was repeatedly fired off the coast of Washington state, and the resulting acoustic fields were recorded by a nominal 8 km long, 636-element towed horizontal array. Based on hundreds of airgun firings from a primarily shore-parallel transect, both autoproducts were found to extend field coherence to frequencies outside the genuine field’s bandwidth and to produce longer coherence lengths than genuine fields, in most cases. When used for matched-field processing, the same data illustrate the benefits of the autoproducts’ extended coherence.

Copyright of Builder (1896-0642) is the property of PWB MEDIA Zdzieblowski sp.j. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

When analyzing the transmission characteristics of LEDs for long-distance lighting and communication applications, the light field is commonly assumed to be fully incoherent. However, in reality, the LED light source emits partially coherent light with a spatial coherence length on the order of microns. This paper is based on the generalized higher-order Lambert model of LEDs and aims to construct a Gaussian-Schell model for the LED beam (LED-GSM) on the near-field source plane, with a half-power angle of no more than 10o. Utilizing the cross-spectral density function transmission theory for partially coherent light, this paper provides the LED-GSM model’s spatial coherence length and beam radius at different distances and designs an experiment for measuring the spatial coherence length of LED beams. Experimental measurements of the spatial coherence length and beam spot size of LED beams at different distances are carried out using a Thorlabs LED528EHP light source. The experimental results match well with the theoretical simulations of the LED-GSM model, thus validating its effectiveness. Then, the proposed LED-GSM model is utilized to investigate the long-distance transmission characteristics of partially coherent narrow-beam LED light. Simulation results indicate that the spatial coherence length of the LED light field can reach tens to hundreds of millimeters over transmission distances of several kilometers. The beam radius is much smaller than that of the beam radius based on the fully incoherent model, and the beam intensity distribution also displays distinct differences.

Wind tunnel tests remain crucial to solving the wind-induced issues, such as buffeting. The turbulence impacts on the aerodynamic forces is vital to buffeting responses of a bridge, which has been neglected, for that traditional passive wind tunnel test simulations are mainly to perform smaller turbulence integral scale, compared with the reduced-scale similarity. A turbulence hybrid simulation device that integrates vibrating grids and active fans was proposed, realizing a detectable adjustment of the bi-directional pulse energy of the incoming turbulence. The simulation development of the active turbulence in the wind tunnel test was reviewed briefly firstly. To investigate turbulence influence on the aerodynamic forces, the pressure-measurement wind tunnel tests of typical bridge decks were carried out in active control wind tunnel. The impacts of different incoming turbulence on the aerodynamic force and buffeting response were furtherly discussed. Results revealed that the bi-direction (along-wind and vertical wind) influenced aerodynamic forces synergistically. Otherwise, turbulence integral scale strongly influenced aerodynamic characteristics, such as buffeting responses, notably, the buffeting responses obtained in active controlled wind tunnel would be reasonable for a safety evaluation of bridges under construction and operation. [ABSTRACT FROM AUTHOR]

RESUME: L'Outil de Suivi et de Surveillance des Étiages en Cohérence sur le Rhône (OSSEC Rhône) est un outil permettant de caractériser en temps réel les événements d'étiage sur le Rhône et ses principaux affluents. OSSEC repose sur une caractérisation locale des étiages à partir d'un seuil, puis sur la mise en cohérence des étiages locaux au sein d'une plus grande zone spatiale. Cette méthode a été adaptée au cas du bassin versant rhodanien, qui possède des données anthropisées et une dépendance amont-aval. Cette caractérisation permet d'obtenir, pour chaque station hydrologique, les dates de début, de fin, et la sévérité de chaque étiage, en cohérence sur l'ensemble du bassin du Rhône. Lancé en temps réel, OSSEC Rhône récupère les dernières données de débit acquises et lance la méthodologie depuis le dernier événement caractérisé. L'outil compare ensuite l'événement en cours avec un historique d'événements déjà sauvegardé. Des figures sont générées puis sélectionnées par l'opérateur afin d'établir la chronologie et l'évolution de l'événement en cours. OSSEC Rhône permet d'approfondir les connaissances des étiages, en les caractérisant de façon plus complète que de simples statistiques de débit. Les événements obtenus étant spatialement cohérents, il est alors possible d'étudier leur évolution saisonnière ou leur fréquence. OSSEC Rhône is a tool for monitoring and characterising low-flow events on the Rhône River and its tributaries in real time. Based on daily streamflow series, low-flow events are characterised for each hydrological station, by a threshold method. This method provides a beginning and ending date, as well as the severity of each identified event. Then, based on an overlapping of dates, events are spatially matched across stations to identify spatio-temporal events on the Rhône tributaries. Lastly, these are matched to the events identified on the Rhône River. These three steps ensure consistency between low-flow events of the main river and of its tributaries. In real time, OSSEC retrieves streamflow data and launches the methodology since the last characterized event in the archive. It can then determine whether a low-flow event is currently underway, and its inception date, duration, and severity. The selected event is then compared to other historical events. OSSEC Rhône makes it possible to deepen the knowledge of such events by going beyond simple streamflow statistics, usually computed at the monthly scale. OSSEC Rhône is therefore a decision-making tool for water managers, allowing a day-by-day assessment of the spatial evolution of a low-flow event throughout a year. [ABSTRACT FROM AUTHOR]

The low‐spatial‐coherence imaging capability of computer‐generated holography (CGH) is a key to high‐resolution displays, virtual reality, augmented reality, and holographic microscopy. The low spatial coherence caused by complex disturbances can damage the image quality irreversibly. The optical field with low spatial coherence has large fluctuations, making it difficult to be quantified and modeled directly. To tackle these challenges, a deep neural network‐based model U‐residual dense network (U‐RDN) is proposed, which obtains the optimal solution under the low‐spatial‐coherence condition. The large‐scale images are generated using optical experiments, with analysis and restoration by deep learning. Extensive experiments demonstrate the strong out‐of‐distribution robustness of U‐RDN, which is generalizable to unseen classes in unseen domains. The learning‐based approach and low‐spatial‐coherence dataset open a new path toward the next generation of CGH.

To suppress the noise and sidelobe of photoacoustic images, a method is proposed combined with spatial coherence and polarity coherence. In this method, PA signals are delayed, multiplied, then performed polarity coherence, and finally summed. The polarity of delayed-and-multiplied signals rather than the amplitude is considered in polarity coherence operation. The polarity coherence factor is calculated based on the standard deviation of the polarity. Then, the factor as weights is applied to the coherent sum output after spatial autocorrelation to finally obtain the image. The simulated and experimental results prove that the noise level can be effectively suppressed due to its relatively low polarity coherence factor. Compared with the delay-and-sum method, the quantitative results in simulations show that the image contrast and full-width at half-maximum of the proposed method increase by about 227.0 % and 56.5 % when the signal-to-noise ratio of the raw signal is 0 dB, respectively. Besides achieving a better image contrast, this method obtains improvements in sidelobe attenuation and has a narrow main lobe.

Copyright of Journal of Signal Processing is the property of Journal of Signal Processing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We propose Graph-Cut RANSAC, GC-RANSAC in short, a new robust geometric model estimation method where the local optimization step is formulated as energy minimization with binary labeling, applying the graph-cut algorithm to select inliers. The minimized energy reflects the assumption that geometric data often form spatially coherent structures – it includes both a unary component representing point-to-model residuals and a binary term promoting spatially coherent inlier-outlier labelling of neighboring points. The proposed local optimization step is conceptually simple, easy to implement, efficient with a globally optimal inlier selection given the model parameters. Graph-Cut RANSAC, equipped with “the bells and whistles” of USAC and MAGSAC++, was tested on a range of problems using a number of publicly available datasets for homography, 6D object pose, fundamental and essential matrix estimation. It is more geometrically accurate than state-of-the-art robust estimators, fails less often and runs faster or with speed similar to less accurate alternatives. The source code is available at https://github.com/danini/graph-cut-ransac. [ABSTRACT FROM AUTHOR]

Tumor growth, similarly to several other pathologies, tends to change the structural orientation of soft tissue fibers, which can become relevant markers for diagnosis. Current diagnosis protocols may require a biopsy for histological analysis, which is an invasive, painful and stressful procedure with a minimum turnaround time of 2 d. Otherwise, diagnosis may involve the use of complex methods with limited availability such as diffusion tensor imaging (magnetic resonance diffusion tensor imaging), which is not widely used in medical practice. Conversely, advanced methodologies in ultrasound imaging such as backscatter tensor imaging (BTI) might become a routine procedure in clinical practice at a limited cost. This method evaluates the local organization of soft tissues based on the spatial coherence of their backscattered ultrasonic echoes. Previous work has proven that BTI applied with matrix probes enables measurement of the orientation of soft tissue fibers, especially in the myocardium. The aims of the study described here were (i) to present for the first time a methodology for performing BTI in a volume on ex vivo human breast tumors using a linear probe and (ii) to display a first proof of concept of the link between BTI measurements and the orientation of collagen fibers. [ABSTRACT FROM AUTHOR]

The frequency-difference and frequency-sum autoproducts, quadratic products of complex acoustic field amplitudes at two frequencies, may mimic genuine acoustic fields at the difference and sum frequencies of the constituent fields, respectively. Autoproducts have proven useful in extending the useable frequency range for acoustic remote sensing to frequencies outside a recorded field's bandwidth. In array signal processing applications, the spatial coherence of the field often sets performance limits. This paper presents results for the spatial coherence of the genuine field, the frequency-difference autoproduct, and the frequency-sum autoproduct as determined from data collected during the Cascadia Open-Access Seismic Transects (COAST 2012) experiment. In this experiment, an airgun array providing a 10 to 200 Hz signal was repeatedly fired off the coast of Washington state, and the resulting acoustic fields were recorded by a nominal 8 km long, 636-element towed horizontal array. Based on hundreds of airgun firings from a primarily shore-parallel transect, both autoproducts were found to extend field coherence to frequencies outside the genuine field's bandwidth and to produce longer coherence lengths than genuine fields, in most cases. When used for matched-field processing, the same data illustrate the benefits of the autoproducts' extended coherence. [ABSTRACT FROM AUTHOR]

We propose a new video vectorization approach for converting videos in the raster format to vector representation with the benefits of resolution independence and compact storage. Through classifying extracted curves in each video frame into salient ones and non-salient ones, we introduce a novel bipartite diffusion curves (BDCs) representation in order to preserve both important image features such as sharp boundaries and regions with smooth color variation. This bipartite representation allows us to propagate non-salient curves across frames such that the propagation, in conjunction with geometry optimization and color optimization of salient curves, ensures the preservation of fine details within each frame and across different frames, and meanwhile, achieves good spatial-temporal coherence. Thorough experiments on a variety of videos show that our method is capable of converting videos to the vector representation with low reconstruction errors, low computational cost, and fine details, demonstrating our superior performance over the state of the art. We also show that, when used for video upsampling, our method produces results comparable to video super-resolution. [ABSTRACT FROM AUTHOR]

Many spatial applications benefit from the fast answering to a seemingly simple spatial query: “Is a point of interest (POI) ‘in-path’ to the shortest path between a source and a destination?” In this context, an in-path POI is one that is either on the shortest path or can be reached within a bounded yet small detour from the shortest path. The fast answering of the in-path queries is contingent on being able to determine without having to actually compute the shortest paths during runtime. Thus, this requires a precomputation solution. The key contribution of the paper is the development of an in-path oracle that is based on precomputation of which pairs of sources and destinations are in-path with respect to the given POI. For a given road network with n nodes and m POIs, an O(m×n)-sized oracle is envisioned based on the reduction of the well-separated pairs (WSP) decomposition of the road network. Furthermore, an oracle can be indexed in a database using a B-tree that can answer queries at very high throughput. Experimental results on the real road network POI dataset illustrate the superiority of this technique compared to a baseline algorithm. The proposed approach can answer ≈ 1.5 million in-path queries per second compared to a few hundred per second using a suitable baseline approach.

In this study, spatial coherence tunable random lasing is proposed by designing a random laser with separate coupling configuration between the gain medium and the scattering part. By using the polymer dispersion liquid crystal (PDLC) film with tunable scattering coefficient for supplying random scattering feedback and output modification, red, green and blue random lasers are obtained. By applying or removing electric field to manipulate the scattering intensity of the PDLC film, intensity and spatial coherence of these random lasing are then switched between the high or low state. This work demonstrates that controlling the external scattering intensity is an effective method to manipulate the spatial coherence of random lasing. [ABSTRACT FROM AUTHOR]

Rainfall extremes are of major and increasing importance in semi‐arid countries and their variability has strong implications for water resource and climate impacts on the local societies and environment. Here, we examine intraseasonal descriptors (ISDs) and wet extremes in austral summer rainfall (November–February) over South Africa (SA). Using daily observations from 225 rain gauges and ERA5 reanalysis between 1979 and 2015, we propose a novel typology of wet extreme events based on their spatial fraction, thus differentiating large‐ and small‐scale extremes. Long‐term variability of both types of extreme rainfall events is then extensively discussed in the context of ISDs. The results demonstrate that using 7% of spatial fraction simultaneously exceeding the local threshold of the 90th percentile produces remarkable results in characterizing rainfall extremes into large‐ and small‐scale extremes. Austral summer total rainfall is found to be primarily shaped by large‐scale extremes which constitute more than half of the rainfall amount under observation, and nearly half in ERA5. Observation (ERA5) shows an average of 8 ± 5 (20 ± 7) days per season associated with large‐scale extremes, which are comprised in 5 ± 3 (10 ± 3) spells with an average persistence of at least 2 days. Overall, we find a strong dependence of total rainfall on the number of wet days and wet spells that are associated with large‐scale extremes. We also find that large‐ and small‐scale extremes are well‐organized and spatially coherent in nature yet extreme conditions during small‐scale events are found sporadic over the region, contrasting with large‐scale events for which extreme conditions are found over a larger and coherent region. [ABSTRACT FROM AUTHOR]

Multi-covariate imaging of sub-resolution targets (MIST) is a statistical, model-based image formation technique that smooths speckles and reduces clutter. MIST decomposes the measured covariance of the element signals into modeled contributions from mainlobe, sidelobes, and noise. MIST covariance models are derived from the well-known autocorrelation relationship between transmit apodization and backscatter covariance. During in vivo imaging, the effective transmit aperture often deviates from the applied apodization due to nonlinear propagation and wavefront aberration. Previously, the backscatter correlation length provided a first-order measure of these patient-specific effects. In this work, we generalize and extend this approach by developing data-adaptive covariance estimation, parameterization, and model-formation techniques. We performed MIST imaging using these adaptive models and evaluated the performance gains using 152 tissue-harmonic scans of fetal targets acquired from 15 healthy pregnant subjects. Compared to standard MIST imaging, the contrast-to-noise ratio (CNR) is improved by a median of 8.3%, and the speckle signal-to-noise ratio (SNR) is improved by a median of 9.7%. The median CNR and SNR gains over B-mode are improved from 29.4% to 40.4% and 24.7% to 38.3%, respectively. We present a versatile empirical function that can parameterize an arbitrary speckle covariance and estimate the effective coherent aperture size and higher order coherence loss. We studied the performance of the proposed methods as a function of input parameters. The implications of system-independent MIST implementation are discussed. [ABSTRACT FROM AUTHOR]

Velocity analysis using the semblance spectrum can provide an effective velocity model for advanced seismic imaging technology, in which the picking accuracy of velocity analysis is significantly affected by the resolution of the semblance spectrum. However, the peak broadening of the conventional semblance spectrum leads to picking uncertainty, and it cannot deal with the amplitude-variation-with-offset (AVO) phenomenon. The well-known AB semblance can process the AVO anomalies, but it has a lower resolution compared with conventional semblance. To improve the resolution of the AB semblance spectrum, we propose a new weighted AB semblance based on principal component analysis (PCA). The principal components or eigenvalues of seismic events are highly sensitive to the components with spatial coherence. Thus, we utilized the principal components of the normal moveout (NMO)-corrected seismic events with different scanning velocities to construct a weighting function. The new function not only has a high resolution for velocity scanning, but it is also a friendly method for the AVO phenomenon. Numerical experiments with the synthetic and field seismic data sets proved that the new method significantly improves resolution and can provide more accurate picked velocities compared with conventional methods. [ABSTRACT FROM AUTHOR]

Human motion prediction aims to generate future motions based on the observed human motions. Witnessing the success of Recurrent Neural Networks (RNN) in modeling sequential data, recent works utilize RNNs to model human-skeleton motions on the observed motion sequence and predict future human motions. However, these methods disregard the existence of the spatial coherence among joints and the temporal evolution among skeletons, which reflects the crucial characteristics of human motions in spatiotemporal space. To this end, we propose a novel Skeleton-Joint Co-Attention Recurrent Neural Networks (SC-RNN) to capture the spatial coherence among joints, and the temporal evolution among skeletons simultaneously on a skeleton-joint co-attention feature map in spatiotemporal space. First, a skeleton-joint feature map is constructed as the representation of the observed motion sequence. Second, we design a new Skeleton-Joint Co-Attention (SCA) mechanism to dynamically learn a skeleton-joint co-attention feature map of this skeleton-joint feature map, which can refine the useful observed motion information to predict one future motion. Third, a variant of GRU embedded with SCA collaboratively models the human-skeleton motion and human-joint motion in spatiotemporal space by regarding the skeleton-joint co-attention feature map as the motion context. Experimental results of human motion prediction demonstrate that the proposed method outperforms the competing methods. [ABSTRACT FROM AUTHOR]

Traditional pulse-echo ultrasound imaging heavily relies on the discernment of signals based on their relative magnitudes but is limited in its ability to mitigate sources of image degradation, the most prevalent of which is acoustic clutter. Advances in computing power and data storage have made it possible for echo data to be alternatively analyzed through the lens of spatial coherence, a measure of the similarity of these signals received across an array. Spatial coherence is not currently explicitly calculated on diagnostic ultrasound scanners but a large number of studies indicate that it can be employed to describe image quality, to adaptively select system parameters and to improve imaging and target detection. With the additional insights provided by spatial coherence, it is poised to play a significant role in the future of medical ultrasound. This review details the theory of spatial coherence in pulse-echo ultrasound and key advances made over the last few decades since its introduction in the 1980s. [ABSTRACT FROM AUTHOR]

In the context of energy industry decentralization, electrical networks encounter deviations of power quality indices (PQI), including violations of the sinusoidality of current and voltage signals, which increase errors in the joint digital processing of spatially separated signals in digital devices. This paper addresses specific features of using the concept of spatial coherence in the measurement and digital processing of current and voltage signals. Methods for assessing the coherence of current and voltage signals during synchronized measurements are considered for the case of PQI deviation. The example of a double-ended transmission line fault location (hereafter, DTLFL) demonstrates that the lower the cross-correlation coefficient, the higher the error and the lower the accuracy of calculating the distance to the fault site. The nature of the influence of spatial coherence violations on errors in DTLFL depends on the expression used to calculate the distance to the fault point. The application of a normalized cross-correlation coefficient for finding errors in the digital processing of current and voltage signals, in the case of spatial coherence violation, was substantiated. The influence of interharmonics and noise on errors in DTLFL, in the case of violations of spatial coherence of signals, was investigated. The magnitude of distortions and error in estimating the current and voltage amplitude depends on the ratio between the amplitudes and phases of the fundamental and distorting interharmonics. Filtration of the original and decimated signals based on the discrete Fourier transform eliminates the noise components of the power frequency harmonics. [ABSTRACT FROM AUTHOR]

In this work, we present an introduction to the field of spatially partial coherent beams, while keeping in mind the transverse structure of an optical field. We look closely at the concept of spatial coherence and show some strategies to deal with it. We work stepâ€"byâ€"step with the reader and construct as an example, a partially coherent vortex beam. Finally, using numerical simulations, the richness in structure of a partially coherent field is revealed through its crossâ€"correlation function. [ABSTRACT FROM AUTHOR]

Thermal noise and acoustic clutter signals degrade ultrasonic image quality and contribute to unreliable clinical assessment. When both noise and clutter are prevalent, it is difficult to determine which one is a more significant contributor to image degradation because there is no way to separately measure their contributions in vivo. Efforts to improve image quality often rely on an understanding of the type of image degradation at play. To address this, we derived and validated a method to quantify the individual contributions of thermal noise and acoustic clutter to image degradation by leveraging spatial and temporal coherence characteristics. Using Field II simulations, we validated the assumptions of our method, explored strategies for robust implementation, and investigated its accuracy and dynamic range. We further proposed a novel robust approach for estimating spatial lag-one coherence. Using this robust approach, we determined that our method can estimate the signal-to-thermal noise ratio (SNR) and signal-to-clutter ratio (SCR) with high accuracy between SNR levels of −30 to 40 dB and SCR levels of −20 to 15 dB. We further explored imaging parameter requirements with our Field II simulations and determined that SNR and SCR can be estimated accurately with as few as two frames and sixteen channels. Finally, we demonstrate in vivo feasibility in brain imaging and liver imaging, showing that it is possible to overcome the constraints of in vivo motion using high-frame rate M-Mode imaging. [ABSTRACT FROM AUTHOR]

Ultrasound is an essential tool for diagnosing and monitoring diseases, but it can be limited by poor image quality. Lag-one coherence (LOC) is an image quality metric that can be related to signal-to-noise ratio and contrast-to-noise ratio. In this study, we examine matched LOC and B-mode images of the liver to discern patterns of low image quality, as indicated by lower LOC values, occurring beneath the abdominal wall, near out-of-plane vessels and adjacent to hyperechoic targets such the liver capsule. These regions of suppressed coherence are often occult; they present as temporally stable uniform speckle on B-mode images, but the LOC measurements in these regions suggest substantially degraded image quality. Quantitative characterization of the coherence suppression beneath the abdominal wall reveals a consistent pattern both in simulations and in vivo; sharp drops in coherence occurring beneath the abdominal wall asymptotically recover to a stable coherence at depth. Simulation studies suggest that abdominal wall reverberation clutter contributes to the initial drop in coherence but does not influence the asymptotic LOC value. Clinical implications are considered for contrast loss in B-mode imaging and estimation errors for elastography and Doppler imaging. [ABSTRACT FROM AUTHOR]

Diffuse reverberation clutter often significantly degrades the visibility of abdominal structures. Reverberation clutter acts as a temporally stationary haze that originates from the multiple scattering within the subcutaneous layers and has a narrow spatial correlation length. We recently presented an adaptive beamforming technique, Lag-one Spatial Coherence Adaptive Normalization (LoSCAN), which can recover the contrast suppressed by incoherent noise. LoSCAN successfully suppressed reverberation clutter in numerous clinical examples. However, reverberation clutter is a 3-D phenomenon and can often exhibit a finite partial correlation between receive channels. Due to a strict noise-incoherence assumption, LoSCAN does not eliminate correlated reverberation clutter. This work presents a 2-D matrix array-based LoSCAN method and evaluates matrix-LoSCAN-based strategies to suppress partially correlated reverberation clutter. We validated the proposed matrix LoSCAN method using Field II simulations of a ${64}\times {64}$ symmetric 2-D array. We show that a subaperture beamforming (SAB) method tuned to the direction of noise correlation is an effective method to enhance LoSCAN’s performance. We evaluated the efficacy of the proposed methods using fundamental and harmonic channel data acquired from the liver of two healthy volunteers using a ${64}\times {16}$ custom 2-D array. Compared to azimuthal LoSCAN, the proposed approach increased the contrast by up to 5.5 dB and the generalized contrast-to-noise ratio (gCNR) by up to 0.07. We also present analytic models to understand the impact of partially correlated reverberation clutter on LoSCAN images and explain the proposed methods’ mechanism of image quality improvement. [ABSTRACT FROM AUTHOR]

Background: The coherent plane wave compounding (CPWC) is a promising technique to enhance the imaging quality while maintaining the high frame rate in the plane wave ultrasound imaging. Recently, the spatial-coherence-based method has been specially designed to process echo matrix required by the minimum variance (MV) method.Objective: In this paper, a novel beamforming method that integrates the submatrix-spatial-coherence-based MV with the sign coherence factor (SCF) is proposed to further improve the imaging quality.Method: The submatrix smoothing technique is modified to smooth and de-correlate signals of the receiving array dimension. Then, the SCF is used to modify the input vector of the beamformer, which can reduce side lobe noises with almost no increase in the amount of calculation. Simulation, phantom, in vivo, and sound velocity error experiments have been performed to verify the superiority of the proposed beamformer.Results: The imaging results show that the proposed approach performs better in the imaging resolution and contrast compared to the traditional CPWC method.Conclusion: The robustness of the proposed method is enhanced, and the over-suppression phenomenon can be alleviated, which is a phenomenon that occurs in the original spatial-coherence and SCF methods. [ABSTRACT FROM AUTHOR]

Subwavelength motion estimation is vital for the production of focused synthetic aperture sonar (SAS) imagery. The required precision is obtainable from the sonar data itself through a process termed micronavigation. Along-track micronavigation is achieved by a similar technique to that used in correlation velocity logs (CVLs), where sparse estimates of the spatial coherence function are interpolated to estimate the location of the peak coherence and hence estimate the interping vehicle motion. However, along-track micronavigation estimates made using this technique are biased, which limits the utility of these measurements for long-term navigation of autonomous underwater vehicles (AUVs). Three sources of along-track motion estimation bias are considered in this article. First, imperfect temporal registration between the signals results in coherence estimates that are negatively biased as a function of the temporal offset. Second, the sparse estimates of the spatial coherence function are obtained by cross-correlation of complex baseband signals, a process which is known to result in positively biased coherence estimates, especially when the true coherence is low. Finally, mismatches between the underlying spatial coherence function and the interpolation kernel used to estimate the peak coherence location also result in along-track micronavigation bias. In this article, we describe and evaluate three methods for reducing along-track micronavigation bias. We introduce a temporal registration of the signals before coherence estimation, which reduces the impact of negative coherence bias due to temporal offsets. The remaining coherence estimation bias is reduced by combining multiple coherence estimates in a Bayesian coherence estimator. Additionally, an improved interpolation kernel is derived with a significantly improved fit compared to the current gold standard Gaussian interpolation kernel. The improvements in along-track micronavigation accuracy are demonstrated using two simulated data sets, which both allow comparison with ground truth. The first involves direct simulation of the spatial coherence from a given interping geometry using the pulse-echo formulation of the van Cittert–Zernike theorem, while the second involves simulation of raw sonar echo data using a point-scatterer model. Using these simulations, a reduction in along-track micronavigation bias of 48.5%–99.5% is demonstrated, with reductions in along-track micronavigation error standard deviation of up to 34%. This improvement expands the potential for SAS-equipped AUVs to reduce their long-term navigation drift, facilitating longer underwater transits, improved target localization, and reduced track misalignment in repeat-pass operations. [ABSTRACT FROM AUTHOR]

This work demonstrates that the combination of multi-line transmission (MLT) and short-lag spatial coherence (SLSC) imaging improves the contrast of highly coherent structures within soft tissues when compared to both traditional SLSC imaging and conventional delay and sum (DAS) beamforming. Experimental tests with small (i.e., $100~ \mu \text{m}$ –3 mm) targets embedded in homogeneous and heterogeneous backgrounds were conducted. DAS or SLSC images were reconstructed when implementing MLT with varying numbers of simultaneously transmitted beams. In images degraded by acoustic clutter, MLT SLSC achieved up to 34.1 dB better target contrast and up to 16 times higher frame rates when compared to the more conventional single-line transmission SLSC images, with lateral resolution improvements as large as 38.2%. MLT SLSC thus represents a promising technique for clinical applications in which ultrasound visualization of highly coherent targets is required (e.g., breast microcalcifications, kidney stones, and percutaneous biopsy needle tracking) and would otherwise be challenging due to the strong presence of acoustic clutter. [ABSTRACT FROM AUTHOR]

How climate change will affect the spatial coherence of droughts is a key question that water managers must answer in order to adopt strategies to mitigate impacts on water resources. Water transfers from regions with excess to those in deficit are fundamental to such strategies, but only possible if both regions are not simultaneously under drought conditions—these relationships could change in a warming world. Here, we use future simulations (under RCP8.5) of streamflow (186 catchments) and groundwater level (41 boreholes) from the Enhanced Future Flows and Groundwater (eFLaG) dataset to analyse the projected change in the spatial coherence of hydrological droughts at a national scale, with Great Britain as an example. Joint and conditional probabilities of two regions being in drought simultaneously are used to characterise the spatial coherence. The results are sensitive to various uncertainties, including the way drought is defined. However, some key findings emerge. In particular, for droughts defined based on current conditions, our results show that the spatial coherence of streamflow droughts for the ‘far future’ (2050–2089) is expected to increase during the summer everywhere in the country. During the winter, however, spatial coherence may only increase in the South-East, where the sharpest rise in winter droughts is likely to occur. The coherence between groundwater and streamflow droughts shows a more mixed picture, dependant on season and region. One important observation is that, in the South-East during the summer, the proportion of streamflow droughts that coincide with groundwater droughts is expected to decrease. These results provide a valuable insight for water managers to help inform their long-term strategy to overcome future impacts of droughts, including the feasibility of inter-region water transfers and conjunctive use (surface and groundwater) schemes. This flexible methodology has the potential to be applied in other parts of the world to help shape strategic regional and national investments to increase resilience to droughts.

A detailed theoretical and experimental study on the effect of the superposition of uncorrelated speckle patterns with polarization diversity on the spatial statistics of the superposed speckle pattern is presented. It is shown that depending on the mutual orientation of the polarization vectors of the constituent speckle patterns, the maximum degree of coherence (DoC) and degree of polarization (DoP) of the superposed speckle pattern changes between a maximum and minimum value in a sinusoidal fashion. Moreover, the average intensity ratio of the constituent speckle patterns is also found to be affecting these variations. A study of the change in the visibility of the two-point intensity correlation function also reveals a sinusoidal nature of the variation and its dependence on the ratio of the average intensity, which are found to be similar to the variations of the maximum DoC and DoP. A detailed study on the changes in the normalized probability density function is also performed for better understanding of the effect on the spatial statistics.

Miniaturization of attenuated total reflectance (ATR) spectrometers has been an emerging field applying such powerful surface sensing method for in-situ spectroscopic analysis. In this work, we present a model for field propagation through ATR element under the illumination of multimode fiber (MMF) in a micro-electro-mechanical-systems (MEMS) based ATR Fourier transform infrared (FTIR) spectroscopic system. The core spectrometer is based on micro-fabricated Michelson interferometer using deep etching technology, in which the light propagates in-plane with respect to the silicon substrate. An ATR multiple reflection crystal is illuminated with infrared (IR) thermal blackbody radiation source through an MMF. The output light of the crystal is fiber-coupled to the MEMS interferometer then to an IR broadband photodetector. The optical system is modelled using scaler Fourier optics, where the fiber output field is represented by a group of spatially shifted elementary sources, to predict the ATR absorbance response, taking into account the partial spatial coherence nature of the MMF output. The model output leads to the requirements on the ATR measurement conditions and numerical aperture (NA) of the system. The model is compared to practical results of MEMS spectrometer which is experimentally characterized over the mid-infrared (MIR) wavenumber range from 5000 cm−1 to 2100 cm−1, lower limited by the used fiber and photodetector cut-off. Spectra of liquid samples are obtained using two different crystals and total internal reflection (TIR) angles showing good agreement with theoretical prediction. [ABSTRACT FROM AUTHOR]

The spatial coherence of acoustic pressure fields would affect the design of large-aperture sonar systems. The experimental data at low frequencies propagating in approximately 100 m depth water from explosive sources to a bottom-resting hydrophone is analyzed to study the horizontal spatial coherence. Sound paths are about 80 km both in the along-shore direction and in the cross-shore direction. The theoretical analysis interprets that the signals of a single mode after compensating the modal phase would have higher correlation coefficients than the signals including all modes. The warping transformation is used to filter the modes. The experimental results show that the coherence length of a single mode can reach more than 100 km, which corresponds to about 2700–16000 λ due to the frequency. The high correlation of a single mode indicates that it is possible to perform coherent processing on large-aperture arrays or distributed arrays with a maximum horizontal size much larger than the existing array apertures in shallow water. • The theoretical analysis interprets that the signals of a single mode would have higher correlation coefficients. • The experimental results show that the coherence length of a single mode can be about 2700-16000 λ. • The high correlation of a single mode indicates that it is possible to perform coherent processing on large-aperture arrays. [ABSTRACT FROM AUTHOR]

• Enable speckle correlated imaging with high spatial coherent light. • Enhanced field of view attributed to a memory effects-free calculation method. • Overcoming specific plane image reconstruction enables feasible non-mechanical focusing. Flexible fiber-optic lensless endoscopic imaging plays a significant role in medical and biological applications. Lensless imaging based on far-field speckle of multi-core fibers under spatially incoherent light source illumination relied on the angular optical memory effect, resulting in limited field of view and susceptibility to interference effects. Image reconstruction from fiber speckle intensity under the highly coherent light illumination has been investigated using classical coherent diffraction theory, but it imposes limitations on imaging distance and detection positions. However, existing alternative solutions involve reducing coherence level to satisfy the angular optical memory effect, which increases system complexity and sacrifices the advantages of single-frame imaging. The reconstruction of intensity-based images remains a significant challenge under highly coherent illumination, primarily due to the interference effect. In this study, an imaging algorithm that reconstructs the original image solely from the intensity of far-field fiber speckle under coherent illumination conditions is proposed. The proposed method is based on statistical optics theory and aims to extract the relevant information within coherent speckle patterns to reconstruct the image. Our approach expands the imaging field of view, simplifies the imaging setup, and broadens the range of viable light sources for speckle correlation imaging. The effectiveness of the algorithm is verified by simulated experiments and a real imaging system. [ABSTRACT FROM AUTHOR]

In this study, spatial coherence tunable random lasing is proposed by designing a random laser with separate coupling configuration between the gain medium and the scattering part. By using the polymer dispersion liquid crystal (PDLC) film with tunable scattering coefficient for supplying random scattering feedback and output modification, red, green and blue random lasers are obtained. By applying or removing electric field to manipulate the scattering intensity of the PDLC film, intensity and spatial coherence of these random lasing are then switched between the high or low state. This work demonstrates that controlling the external scattering intensity is an effective method to manipulate the spatial coherence of random lasing.

Velocity analysis using the semblance spectrum can provide an effective velocity model for advanced seismic imaging technology, in which the picking accuracy of velocity analysis is significantly affected by the resolution of the semblance spectrum. However, the peak broadening of the conventional semblance spectrum leads to picking uncertainty, and it cannot deal with the amplitude-variation-with-offset (AVO) phenomenon. The well-known AB semblance can process the AVO anomalies, but it has a lower resolution compared with conventional semblance. To improve the resolution of the AB semblance spectrum, we propose a new weighted AB semblance based on principal component analysis (PCA). The principal components or eigenvalues of seismic events are highly sensitive to the components with spatial coherence. Thus, we utilized the principal components of the normal moveout (NMO)-corrected seismic events with different scanning velocities to construct a weighting function. The new function not only has a high resolution for velocity scanning, but it is also a friendly method for the AVO phenomenon. Numerical experiments with the synthetic and field seismic data sets proved that the new method significantly improves resolution and can provide more accurate picked velocities compared with conventional methods.

In the context of energy industry decentralization, electrical networks encounter deviations of power quality indices (PQI), including violations of the sinusoidality of current and voltage signals, which increase errors in the joint digital processing of spatially separated signals in digital devices. This paper addresses specific features of using the concept of spatial coherence in the measurement and digital processing of current and voltage signals. Methods for assessing the coherence of current and voltage signals during synchronized measurements are considered for the case of PQI deviation. The example of a double-ended transmission line fault location (hereafter, DTLFL) demonstrates that the lower the cross-correlation coefficient, the higher the error and the lower the accuracy of calculating the distance to the fault site. The nature of the influence of spatial coherence violations on errors in DTLFL depends on the expression used to calculate the distance to the fault point. The application of a normalized cross-correlation coefficient for finding errors in the digital processing of current and voltage signals, in the case of spatial coherence violation, was substantiated. The influence of interharmonics and noise on errors in DTLFL, in the case of violations of spatial coherence of signals, was investigated. The magnitude of distortions and error in estimating the current and voltage amplitude depends on the ratio between the amplitudes and phases of the fundamental and distorting interharmonics. Filtration of the original and decimated signals based on the discrete Fourier transform eliminates the noise components of the power frequency harmonics.

We present a comprehensive study of the polarization and spatial coherence properties of the lasing modes supported by a four-fold symmetric plasmonic lattice. We can distinguish the scattering induced effects from the lattice geometry induced effects by modifying only the diameter of the particles while keeping the lattice geometry constant. Customized interferometric measurements reveal that the lasing emission undergoes a drastic change from 1D to 2D spatial coherence with increasing particle size, accompanied with dramatic changes in the far field polarization and beaming properties. By utilizing T-matrix scattering simulations, we reveal the physical mechanism governing this transition. In particular, we find that there exists increased radiative coupling in the diagonal directions at the plane of the lattice when the particle diameter is increased. Finally, we demonstrate that the x - and y -polarized (degenerate) lasing modes become phase locked with sufficiently large particles.